EP2596464A1 - Procédé et appareil permettant de créer des recommandations pour un utilisateur - Google Patents
Procédé et appareil permettant de créer des recommandations pour un utilisateurInfo
- Publication number
- EP2596464A1 EP2596464A1 EP11748740.5A EP11748740A EP2596464A1 EP 2596464 A1 EP2596464 A1 EP 2596464A1 EP 11748740 A EP11748740 A EP 11748740A EP 2596464 A1 EP2596464 A1 EP 2596464A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- user
- item
- hierarchy
- categories
- recommendations
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
Definitions
- the present invention relates to a method and apparatus for creating recommendations for a user.
- Broadcasters, web services, software providers, etc, allow users access to free content but, at the same time, expose users to commercial advertisements since advertising is their main source of revenue.
- TV broadcasters offer free TV content to attract viewers but sell advertisement space to advertisers for inserting commercial advertisements between the TV content.
- many web sites offer free services (e.g. Internet searches) to attract visitors to their website but sell space for commercial advertisements in the form of graphical, animated banners or 'sponsored links'.
- advertisements may appeal to users, most of the advertisements are annoying for a user, particularly if the user is not interested in the products or services being advertised.
- the user is mostly interested in the service or content being provided and does not want their experience to be disrupted by advertisements. Users want to feel in control, and in the case of advertisements being automatically placed within or around other content (e.g. web pages, personal TV channels, a user interface, etc), the user likes to have the possibility of not watching the advertisements or even removing the advertisements if he is not interested in them.
- some systems make advertisements more acceptable to the user by targeting the advertisements to this user based on his behavior, his preferences (for example, preferred artist or a movie genre) and, more importantly, to the context in which the advertisements are placed. For example, some systems use keywords, domain names, topics, and demographic targets, etc, specified in a user profile to only place advertisements on websites and web pages containing content that is relevant to the user and, also, to choose advertisements having content that will be of interest to the user (for example, because the content is listed in the user profile or is rated highly in the user profile).
- US 2002/0152463 discloses a system for providing preferred programming events to a user, based on a combination of goodness-of-fit scores associated with categories of a classification hierarchy and a user profile that includes preference scores associated with categories of the classification hierarchy.
- systems such as this are able to provide advertisements to a user that are more likely to be relevant and of interest to the user, there is no guarantee that the system will not render advertisements to the user that the user dislikes or is of no interest to them because a user profile only generally lists content that is liked by a user.
- this is overcome by allowing a user the option to remove a current advertisement, provide an indication that a current advertisement is disliked or to give a poor rating (typically on a two, a five, or a ten star rating scale) to a current advertisement.
- a poor rating typically on a two, a five, or a ten star rating scale
- the system blacklists the current advertisement to prevent it from being rendered to the user in the future and adapts the user profile so that the chance of another advertisement that is similar to the current advertisement being rendered to the user is lower.
- this does not guarantee that advertisements similar to the removed/disliked/poorly rated advertisement will not be rendered to the user in the future because the placement of advertisements depends on a various factors, which the user can only indirectly control.
- the system would require many more negative ratings of other advertisements that are similar to the current advertisement before the system can produce useful recommendations. This means that the user is required to repeatedly indicate to the system that they are not interested in an advertisement and the system requires a relatively high number of ratings before it can produce useful recommendations, which can be frustrating for the user.
- this system allows a user to cease a current advertisement from being rendered, it is difficult for the system to interpret the reasons behind the user making this choice.
- the user may not be interested in the particular product that is the subject of the advertisement (e.g. beer or, more particularly, Heineken beer), the user may not be interested in the particular advertisement, the user may have already seen the advertisement, or the user may not be interested in the entire category of products relating to the subject of the advertisement (e.g. all advertisements about alcoholic beverages or beverages in general).
- the system cannot effectively learn from the actions of the user and the recommendations for a user therefore cannot be improved.
- the invention seeks to provide a method and apparatus that provides an insight into the reasons behind the removal/indication of dislike/poor rating provided by a user regarding an item in order to improve the relevancy of the recommendations provided to the user.
- a method for creating recommendations for a user comprising the steps of: receiving a user input relating to an item; determining, from the metadata of the item, a hierarchy of categories; receiving a rating of at least one category within any one level of the hierarchy; and creating recommendations for the user based on at least the received rating of the at least one category.
- an apparatus for creating recommendations for a user comprising: a user interface for receiving a user input relating to an item; a processor for determining, from the metadata of the item, a hierarchy of categories; the user interface for receiving a rating of at least one category within any one level of the hierarchy; and a recommender for creating
- the user can rate not only the individual item, but any category of the hierarchy, thereby providing the user with an enhanced feeling of control.
- the user can quickly indicate his preferences for entire categories of similar items, thereby providing an insight into the reasons behind the removal, indication of dislike, or poor rating of an item provided to the user. This improves the relevancy of the recommendations provided to the user so that the user is required to rate fewer items before the apparatus can generate useful recommendations.
- the step of determining, from the metadata of the item, a hierarchy of categories may comprise dynamically determining, from the metadata of the item, a hierarchy of categories. In this way, smaller hierarchies related to a single item that include categories that the user actually likes can be created.
- the method may further comprise the step of rendering the determined hierarchy of categories to the user. In this way, the user is able to intuitively navigate the categories to input his ratings regarding one or more of the categories.
- the method may further comprise the step of rendering at least one recommendation to the user based on the created recommendations.
- the step of creating recommendations for a user, based on at least the received rating of the at least one category may comprise updating a user profile and/or updating a blacklist based on the received rating of the at least one category. In this way, the apparatus has a record relating to the inputs received for items and can therefore create more relevant recommendations in the future.
- the user input may include at least one of an indication that the user likes or dislikes the item, a value from a rating scale of degrees of likeness for the item, an instruction to delete the item, an instruction to remove the item. In this way, the user has more control over how to indicate their preferences of items.
- the step of determining, from the metadata of the item, a hierarchy of categories may comprise determining, from the metadata of the item, a plurality of hierarchies of categories, and combining the plurality of hierarchies to determine the hierarchy.
- a hierarchy is determined for each feature (e.g. genre) of the item whose values (e.g. main genre, sub-genre, and sub-sub-genre) can be represented in a hierarchical way. This means that a user is able to indicate the exact features relating to the item that are disliked, which will further improve the relevancy of any recommendations that are provided to the user.
- the item may be one of a webpage, a television program, an advert, an image, a video, or an audio file.
- the apparatus can therefore be used in many applications.
- Figure 1 is a simplified schematic of an apparatus for creating recommendations for a user according to the invention.
- Figure 2 is a flowchart of a method for creating recommendations for a user according to the invention.
- the apparatus 100 comprises a user interface 102 for receiving a user input relating to an item.
- the user interface 102 may be integrated in the apparatus 100 (as shown) or may be separate from the apparatus 100 and wirelessly connected to or wired to the apparatus 100.
- the output of the user interface 102 is connected to a processor 106 and to a recommender 108.
- the output of the processor 106 is connected to a recommender 108.
- the recommender 108 may be wirelessly connected to or wired to an external device 110 via an output channel 112.
- the apparatus 100 may be integrated in the external device 110.
- the external device 110 may be, for example, a TV, a stereo, a computer, a screen, or the like, or a mobile device such as a mobile terminal, a portable TV, or the like.
- the user interface 102 may comprise a rendering device 104 for rendering recommendations to a user.
- the processor 106 may control the external device 110 to render recommendations to a user.
- the processor 106 is connected to a storage device 114.
- the user interface 102 receives a user input relating to an item (step 200).
- the item may be, for example, a webpage, a television program, an advert, an image, a video, an audio file, or the like.
- the user input received by the user interface 102 includes at least one of an indication that the user likes or dislikes the item, a value from a rating scale of degrees of likeness for the item, an instruction to delete/remove the item.
- the user interface 102 communicates the user input to the processor 106 and upon receiving the user input, the processor 106 extracts the metadata of the item to which the user input relates (step 202).
- the item and the metadata of the item are stored in a storage device 114.
- the processor 106 determines a hierarchy of categories from the metadata of the item (step 204).
- the processor 106 may control the storage device 114 to store the determined hierarchy of categories.
- the processor 106 may determine the hierarchy of categories from the metadata of the item. This may involve consulting a local or remote database storing an electronic ontology. For example, the processor 106 may determine the hierarchy using categories associated with the features of the advertisement to create a sub-hierarchy
- the hierarchy shows the categories themselves (e.g. beer), categories in the same level of the hierarchy (e.g. wine, spirits, etc) and categories from higher levels in the hierarchy (alcoholic beverages, beverages, etc) and/or lower levels in the hierarchy (e.g. Heineken beer).
- the creation of the hierarchy by the processor 106 can be made dynamic by, for example, not showing parts of the hierarchy that the user has sufficiently down-rated. For example, if the user has indicated that he dislikes wine a certain number of times or if wine has received a rating lower than a predetermined value, wine will no longer be shown in the hierarchy. In this way, ratings received on previously created hierarchies can be used to create smaller hierarchies related to a single item that include categories that the user actually likes.
- the processor 106 may also determine a plurality of hierarchies of categories from the metadata of the item and combine the plurality of hierarchies to determine the hierarchy.
- the hierarchy is actually a combination of multiple hierarchies, one for each feature of the item whose values can be represented in a hierarchical way.
- the feature "genre" can be represented as a hierarchy that includes the values: main genre, sub-genre, and sub -sub -genre.
- an item may have multiple genres, each having its own hierarchy. For example, a user may not like advertisements with too much action or the like.
- the processor 106 inputs the hierarchy of categories into the recommender
- the processor 106 also inputs the determined hierarchy of categories into the rendering device 104 of the user interface 102 and the rendering device 104 renders the determined hierarchy of categories to the user (step 206).
- the rendering device 104 may be a display that displays the determined hierarchy of categories to the user or the rendering device 104 may be an audio device that outputs the hierarchy of categories to the user in the form of audio.
- the processor 106 may control the external device 110 to render the hierarchy to a user.
- the user interface 102 receives a rating from the user of at least one category within any one level of the hierarchy (step 208) and inputs the rating into the recommender 108.
- the rating may be stored in the storage device 114.
- the recommender 108 creates recommendations for the user based on the received rating of the at least one category (step 210).
- the rating may include at least one of an indication that the user likes or dislikes the category, and a value from a rating scale of degrees of likeness for the category.
- the recommender 108 may, for example, update a user profile and/or update a blacklist based on the received rating of the at least one category. For example, if the user interface 102 receives a rating of a category that is an indication that the user dislikes the category or that is a value from a rating scale of degrees of likeness for the category that is below a predetermined value, the recommender 108 adds the category to a blacklist so that items relating to that category are no longer rendered to the user.
- the recommender 108 updates a user profile to place the category higher in the list of preferences of the user.
- the updated user profile and blacklist can then be used by the recommender 108 to predict ratings for new items.
- the user profile and blacklist may be stored in the storage device 114.
- the recommender 108 outputs the created recommendations into the rendering device 104, which renders at least one recommendation to the user based on the created recommendations (step 212).
- the recommender 108 outputs the created recommendations to the external device 110 via the output channel 112 and controls the external device 110 to render at least one recommendation to the user based on the created recommendations .
- the apparatus 100 can be used to automatically insert targeted advertisements between programs.
- the external device 110 is a TV having a personal channel.
- the personal channel has five programs P1-P5 and two automatically placed advertisements Al and A2.
- the advertisements Al and A2 are placed between the programs P1-P5 as follows:
- Al is an advertisement from "Heineken” and relates to a new beer. Also, the user in this example does not like beer in general, including Heineken beer.
- the user interface 102 receives a negative rating relating to the advertisement Al (step 200).
- the processor 106 extracts the metadata of the advertisement Al (step 202) and determines a hierarchy of categories from the extracted metadata (step 204).
- the rendering device 104 renders the determined hierarchy of categories to the user (step 206). For example, the rendering device 104 presents the hierarchy of categories to the user in the form of a graphical representation, as shown below:
- Heineken beer The user can then give a positive or negative rating at any level of the presented hierarchy via the user interface (step 208). In this way, the user could give a negative rating to "beer” and "Heineken beer” but a positive rating to the other levels if, for example, the user likes wine and would not mind seeing advertisements related to wine products.
- the user is able to select, for each level of the hierarchy, other values for the feature and the particular level. For example, at the second level of the hierarchy "beer”, the user is able select other values such as “wine”, “liquor”, etc, that belong to the upper level “alcoholic beverages” and is able to rate these other values independently.
- the recommender 108 can create recommendations for the user based on the received rating (step 210) including safely deciding which advertisements should not be shown in the channel in the future.
- the apparatus 100 described herein can be applied to TV sets, personal video recorders (PVRs), set-top boxes, audio systems (including portable audio), services
- the apparatus 100 can be applied in many content-based and context- based advertising systems, such as web advertising.
- 'Means' as will be apparent to a person skilled in the art, are meant to include any hardware (such as separate or integrated circuits or electronic elements) or software (such as programs or parts of programs) which reproduce in operation or are designed to reproduce a specified function, be it solely or in conjunction with other functions, be it in isolation or in co-operation with other elements.
- the invention can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the apparatus claim enumerating several means, several of these means can be embodied by one and the same item of hardware.
- 'Computer program product' is to be understood to mean any software product stored on a computer-readable medium, such as a floppy disk, downloadable via a network, such as the Internet, or marketable in any other manner.
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- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Strategic Management (AREA)
- Engineering & Computer Science (AREA)
- Development Economics (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)
Abstract
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP11748740.5A EP2596464A1 (fr) | 2010-07-20 | 2011-07-14 | Procédé et appareil permettant de créer des recommandations pour un utilisateur |
Applications Claiming Priority (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP10170097 | 2010-07-20 | ||
EP11748740.5A EP2596464A1 (fr) | 2010-07-20 | 2011-07-14 | Procédé et appareil permettant de créer des recommandations pour un utilisateur |
PCT/IB2011/053139 WO2012011027A1 (fr) | 2010-07-20 | 2011-07-14 | Procédé et appareil permettant de créer des recommandations pour un utilisateur |
Publications (1)
Publication Number | Publication Date |
---|---|
EP2596464A1 true EP2596464A1 (fr) | 2013-05-29 |
Family
ID=44511126
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP11748740.5A Ceased EP2596464A1 (fr) | 2010-07-20 | 2011-07-14 | Procédé et appareil permettant de créer des recommandations pour un utilisateur |
Country Status (4)
Country | Link |
---|---|
US (1) | US20130124310A1 (fr) |
EP (1) | EP2596464A1 (fr) |
CN (1) | CN102985938A (fr) |
WO (1) | WO2012011027A1 (fr) |
Families Citing this family (9)
Publication number | Priority date | Publication date | Assignee | Title |
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US20130036173A1 (en) * | 2011-08-02 | 2013-02-07 | General Instrument Corporation | Personalizing communications using estimates of the recipient's sensitivity level derived from responses to communications |
US9131355B2 (en) * | 2011-09-30 | 2015-09-08 | Cbs Interactive Inc. | System and method of configuring operations of communication services |
WO2013130834A1 (fr) * | 2012-03-01 | 2013-09-06 | Qloo, Inc. | Système de recommendation à domaines croisés personnalisé |
US9704189B2 (en) * | 2012-09-05 | 2017-07-11 | Rakuten Kobo, Inc. | System and method for a graphical user interface having recommendations |
US10692122B2 (en) * | 2016-03-21 | 2020-06-23 | CarCo Technologies, Inc. | Method and system for facilitating purchase of vehicles by buyers and/or sale of vehicles by sellers |
CN106560825A (zh) * | 2016-05-10 | 2017-04-12 | 徐庆黎 | 老人身体状况评估方法和系统 |
US20180174218A1 (en) * | 2016-12-19 | 2018-06-21 | Sap Se | Recommendation optmization with a dynamic mixture of frequent and occasional recommendations |
US20190066186A1 (en) * | 2017-08-24 | 2019-02-28 | Artivatic Data Labs Private Limited | Cross domain recommendation system and method |
US11358367B2 (en) * | 2018-12-20 | 2022-06-14 | Under Armour, Inc. | Method of forming an article of apparel |
Family Cites Families (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6460036B1 (en) * | 1994-11-29 | 2002-10-01 | Pinpoint Incorporated | System and method for providing customized electronic newspapers and target advertisements |
US6757691B1 (en) * | 1999-11-09 | 2004-06-29 | America Online, Inc. | Predicting content choices by searching a profile database |
US20020152463A1 (en) * | 2000-11-16 | 2002-10-17 | Dudkiewicz Gil Gavriel | System and method for personalized presentation of video programming events |
EP1223757B1 (fr) * | 2001-01-09 | 2006-03-22 | Metabyte Networks, Inc. | Système, procédé et logiciel pour publicité ciblée à l'aide d'une structure de données des profils utilisateur basée sur les préférences de ces utilisateurs |
JP2006526922A (ja) * | 2003-06-02 | 2006-11-24 | コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ | 動的なカテゴリ作成を介した推薦 |
US20070146812A1 (en) * | 2005-12-02 | 2007-06-28 | Lawton Scott S | Reader editable advertising |
US7870026B2 (en) * | 2007-06-08 | 2011-01-11 | Yahoo! Inc. | Selecting and displaying advertisement in a personal media space |
US20080313037A1 (en) * | 2007-06-15 | 2008-12-18 | Root Steven A | Interactive advisory system |
US8538811B2 (en) * | 2008-03-03 | 2013-09-17 | Yahoo! Inc. | Method and apparatus for social network marketing with advocate referral |
US20100100607A1 (en) * | 2008-10-22 | 2010-04-22 | Scholz Martin B | Adjusting Content To User Profiles |
US20100132049A1 (en) * | 2008-11-26 | 2010-05-27 | Facebook, Inc. | Leveraging a social graph from a social network for social context in other systems |
US8375409B2 (en) * | 2009-02-05 | 2013-02-12 | Purplecomm Inc. | Meta channel based media system control technology |
US8352319B2 (en) * | 2009-03-10 | 2013-01-08 | Google Inc. | Generating user profiles |
US8572238B2 (en) * | 2009-10-22 | 2013-10-29 | Sony Corporation | Automated social networking television profile configuration and processing |
US20110153421A1 (en) * | 2009-12-23 | 2011-06-23 | Victor Novikov | Context-Based Selection and Presentation of Social Networking System Content and Advertisements |
US20110185384A1 (en) * | 2010-01-28 | 2011-07-28 | Futurewei Technologies, Inc. | System and Method for Targeted Advertisements for Video Content Delivery |
-
2011
- 2011-07-14 US US13/810,307 patent/US20130124310A1/en not_active Abandoned
- 2011-07-14 WO PCT/IB2011/053139 patent/WO2012011027A1/fr active Application Filing
- 2011-07-14 CN CN2011800353614A patent/CN102985938A/zh active Pending
- 2011-07-14 EP EP11748740.5A patent/EP2596464A1/fr not_active Ceased
Non-Patent Citations (2)
Title |
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None * |
See also references of WO2012011027A1 * |
Also Published As
Publication number | Publication date |
---|---|
WO2012011027A1 (fr) | 2012-01-26 |
CN102985938A (zh) | 2013-03-20 |
US20130124310A1 (en) | 2013-05-16 |
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